影像学

• 全球首发！武汉19-nCoV 肺炎影像学表现
• 深度学习用于新冠肺炎CT诊断效果如何？性能好，用时少—武大人民医院medRxiv论文揭示：有可为
• Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study
• 重大进展 | 中国CHESS多中心合作，首次报道基于AI 机器学习的影像组学模型对COVID-19肺炎住院时间的预测价值
• Machine learning-based CT radiomics model for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: A multicenter study
• 72小时紧急驰援：CT+AI攻破新冠肺炎「假阴性」困境 | AI战疫
• AI战疫 | 清华团队研发新冠肺炎智能检测与分级系统
• 新冠肺炎诊断挑战医疗系统负荷，以下23种肺炎CT智能方案成重要辅助诊断手段
• AI可以如何抗击新冠？WHO论文告诉你这三大场景大有可为
• 使用Keras，TensorFlow诊断COVID-19
• 滑铁卢大学发布《新冠肺炎卷积神经网络COVID-Net》一种定制的新冠深度卷积神经网络设计，用于从胸片图像中检测COVID-19
• COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images
• COVID-Net model for COVID-19 detection on COVIDx dataset
• COVID-19感染肺炎的临床特征和影像学表现
• Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19):A multi-center study in Wenzhou city, Zhejiang, China
• 新冠CT判读准确率达96%，阿里AI是怎么做到的？| AICon
• COVID-19 Image Data Collection
• 号称准确率97%的开源肺炎检测模型：照搬PyTorch教程、50张图片就训练完了
• 四天三夜横穿疫区千里，这两个中国男人亲自把AI新冠方案送到了意大利人手里
• COVID-CT-Dataset: A CT Scan Dataset about COVID-19
• Automated lung segmentation in CT under presence of severe pathologies
• Automatic lung segmentation in routine imaging is a data diversity problem, not a methodology problem
• 想研究新冠CT找不到数据集？UCSD、Petuum开源COVID-CT 数据集
• Classification for covid-19 chest X-ray images using Lightning
• Opacity detection (pneumonia) on chest x-ray
• COVID-19 Imaging-based AI Research Paper Collection
• 新加坡首次公布扫描影像，新冠患者肺部出现“碎石路”
• TensorFlow.js 助力医学影像学
• Weakly Supervised Geodesic Segmentation of Egyptian Mummy CT Scans
• CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
• AI+医学影像应用全景扫描：除自动识别病灶，还支持放射治疗、手术路径规划等
• 计算机视觉用于新冠病毒COVID-19的控制综述，25页pdf
• Computer Vision for COVID-19 Control: A Survey
• Cell重磅 | 开拓新领域，中国多单位合作，张康发现用AI系统能提前识别出潜在的新冠肺炎重症患者，对于减少死亡率有重大临床意义
• Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements and Prognosis of COVID-19 Pneumonia Using Computed Tomography
• Deep Learning for Screening COVID-19 using Chest X-Ray Images
• MedicalZooPytorch: A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
• Chest computed tomography in children with COVID-19 respiratory infection
• POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)
• Is there a role for lung perfusion [99mTc]-MAA SPECT/CT to rule out pulmonary embolism in COVID-19 patients with contraindications for iodine contrast?
• Clinical and radiological changes of hospitalised patients with COVID-19 pneumonia from disease onset to acute exacerbation: a multicentre paired cohort study
• AI 诊断 CT 影像准确率达 96%，医疗AI落地还有哪些挑战与解决方案？| AICon
• COVID-19 lung alterations still evident at 60-day follow-up chest CT in asymptomatic patients despite negative rRT-PCR testing
• Deep Learning in Medical Imaging and Medical Image Analysis
• COVID-19影像学精选图书|章节限时免费开放下载
• 专家视点 | 人工智能在医学图像中的应用：机会与挑战
• 3S战“疫”|用AI诊断新冠肺炎CT影像
• 作者采访 | 深度学习算法应用于COVID-19影像学诊断
• Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation
• 雄起！振奋人心，广州医科大学连续发表6篇Cell，在胆道闭锁，新冠肺炎，结肠炎等领域取得重大突破
• Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software
• AI和放射学精选合集 | Springer Journal
• 深度学习下的医学影像分割算法综述
• 【金猿技术展】肺炎AI医学辅助诊断技术——Dr.Wise®
• COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction
• 基于深度学习的新型冠状病毒肺炎诊断研究综述
• 深度学习在医学影像智能处理中的应用与挑战
• 共识声明：新冠病毒大流行期间，胸部影像学检查在患者管理中的作用
• The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic: A Multinational Consensus Statement From the Fleischner Society
• 严重的COVID-19新冠肺炎幸存者的胸部X线照片不能很好地预测呼吸道症状和功能障碍
• Chest radiography is a poor predictor of respiratory symptoms and functional impairment in survivors of severe COVID-19 pneumonia